Section 1 : Introduction
Lecture 1 About Certification
Lecture 2 Curriculum Overview 00:03:01 Duration
Lecture 3 Installation and Setup Lecture 00:11:43 Duration
Lecture 4 FAQ - Frequently Asked Questions

Section 2 : Python Text Basics
Lecture 1 Introduction to Python Text Basics 00:00:31 Duration
Lecture 2 Working with Text Files with Python - Part One.
Lecture 3 Working with Text Files with Python - Part Two. 00:20:33 Duration
Lecture 4 Working with PDFs 00:12:27 Duration
Lecture 5 Regular Expressions Part One 00:15:12 Duration
Lecture 6 Regular Expressions Part Two 00:10:29 Duration
Lecture 7 Python Text Basics - Assessment Overview 00:02:17 Duration
Lecture 8 Python Text Basics - Assessment Solutions 00:06:48 Duration

Section 3 : Natural Language Processing Basics
Lecture 1 Introduction to Natural Language Processing 00:00:33 Duration
Lecture 2 Spacy Setup and Overview 00:07:17 Duration
Lecture 3 What is Natural Language Processing
Lecture 4 Spacy Basics
Lecture 5 Tokenization - Part One 00:15:32 Duration
Lecture 6 Tokenization - Part Two 00:06:07 Duration
Lecture 7 Stemming 00:09:17 Duration
Lecture 8 Lemmatization 00:06:26 Duration
Lecture 9 Stop Words 00:04:50 Duration
Lecture 10 Phrase Matching and Vocabulary - Part One 00:14:26 Duration
Lecture 11 Phrase Matching and Vocabulary - Part Two 00:06:36 Duration
Lecture 12 NLP Basics Assessment Overview 00:02:39 Duration
Lecture 13 NLP Basics Assessment Solution 00:07:33 Duration

Section 4 : Part of Speech Tagging and Named Entity Recognition
Lecture 1 Introduction to Section on POS and NER 00:00:26 Duration
Lecture 2 Part of Speech Tagging
Lecture 3 Visualizing Part of Speech 00:05:59 Duration
Lecture 4 Named Entity Recognition - Part One 00:09:52 Duration
Lecture 5 Named Entity Recognition - Part Two 00:09:14 Duration
Lecture 6 Visualizing Named Entity Recognition 00:07:05 Duration
Lecture 7 Sentence Segmentation 00:15:54 Duration
Lecture 8 Part Of Speech Assessment 00:02:14 Duration
Lecture 9 Part Of Speech Assessment - Solutions 00:08:17 Duration

Section 5 : Text Classification
Lecture 1 Introduction to Text Classification 00:00:44 Duration
Lecture 2 Machine Learning Overview 00:09:48 Duration
Lecture 3 Classification Metrics 00:11:49 Duration
Lecture 4 Confusion Matrix 00:09:44 Duration
Lecture 5 Scikit-Learn Primer - How to Use SciKit-Learn 00:04:12 Duration
Lecture 6 Scikit-Learn Primer - Code Along Part One 00:15:16 Duration
Lecture 7 Scikit-Learn Primer - Code Along Part Two 00:08:40 Duration
Lecture 8 Text Feature Extraction Overview 00:06:15 Duration
Lecture 9 Text Feature Extraction - Code Along Implement 00:14:24 Duration
Lecture 10 Text Feature Extraction - Code Along - Part Tw 00:10:52 Duration
Lecture 11 Text Classification Code Along Project 00:01:02 Duration
Lecture 12 Text Classification Assessment Overview 00:10:50 Duration
Lecture 13 Text Classification Assessment Solutions 00:06:29 Duration

Section 6 : Semantics and Sentiment Analysis
Lecture 1 Introduction to Semantics and Sentiment Analys 00:00:26 Duration
Lecture 2 Overview of Semantics and Word Vectors 00:07:31 Duration
Lecture 3 Semantics and Word Vectors with Spacy 00:17:11 Duration
Lecture 4 Sentiment Analysis Overview 00:04:38 Duration
Lecture 5 Sentiment Analysis with NLTK 00:13:05 Duration
Lecture 6 Sentiment Analysis Code Along Movie Review Pro 00:07:39 Duration
Lecture 7 Sentiment Analysis Project Assessment 00:02:41 Duration
Lecture 8 Sentiment Analysis Project Assessment - Soluti 00:11:04 Duration

Section 7 : Topic Modeling
Lecture 1 Introduction to Topic Modeling Section 00:00:33 Duration
Lecture 2 Overview of Topic Modeling 00:01:57 Duration
Lecture 3 Latent Dirichlet Allocation Overview 00:10:39 Duration
Lecture 4 Latent Dirichlet Allocation with Python - Part 00:08:49 Duration
Lecture 5 Latent Dirichlet Allocation with Python - Part 00:16:27 Duration
Lecture 6 Non-negative Matrix Factorization Overview 00:06:48 Duration
Lecture 7 Non-negative Matrix Factorization with Python 00:11:37 Duration
Lecture 8 Topic Modeling Project - Overview 00:03:36 Duration
Lecture 9 Topic Modeling Project - Solutions 00:06:32 Duration

Section 8 : Deep Learning for NLP
Lecture 1 Introduction to Deep Learning for NLP 00:00:47 Duration
Lecture 2 The Basic Perceptron Model 00:05:07 Duration
Lecture 3 Introduction to Neural Networks 00:06:30 Duration
Lecture 4 Keras Basics - Part One 00:13:39 Duration
Lecture 5 Keras Basics - Part Two 00:05:15 Duration
Lecture 6 Recurrent Neural Network Overview 00:07:42 Duration
Lecture 7 LSTMs, GRU, and Text Generation
Lecture 8 Text Generation with LSTMs with Keras and Pyth 00:16:18 Duration
Lecture 9 Text Generation with LSTMs with Keras and Pyth 00:12:22 Duration
Lecture 10 Text Generation with LSTMS with Keras - Part T 00:13:51 Duration
Lecture 11 Chat Bots Overview 00:07:12 Duration
Lecture 12 Creating Chat Bots with Python - Part One 00:10:23 Duration
Lecture 13 Creating Chat Bots with Python - Part Two 00:12:52 Duration
Lecture 14 Creating Chat Bots with Python - Part Three 00:16:43 Duration
Lecture 15 Creating Chat Bots with Python - Part Four 00:18:04 Duration